<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Graph Computing | Advanced Computing and Architecture</title><link>https://www.acal.org.cn/en/tags/graph-computing/</link><atom:link href="https://www.acal.org.cn/en/tags/graph-computing/index.xml" rel="self" type="application/rss+xml"/><description>Graph Computing</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 01 Jan 2025 00:00:00 +0000</lastBuildDate><image><url>https://www.acal.org.cn/media/logo_hu_9c369f2c5735daea.png</url><title>Graph Computing</title><link>https://www.acal.org.cn/en/tags/graph-computing/</link></image><item><title>Big Data Mining &amp; Intelligent Computing</title><link>https://www.acal.org.cn/en/research/data-mining/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://www.acal.org.cn/en/research/data-mining/</guid><description>&lt;h2 id="overview"&gt;Overview&lt;/h2&gt;
&lt;p&gt;We research efficient graph stream algorithms, game-theoretic optimization in social networks, personalized recommendation systems, and multimodal knowledge graph completion for large-scale network data and multi-source heterogeneous information, providing theoretical and methodological support for data-driven scientific discovery.&lt;/p&gt;
&lt;h2 id="research-directions"&gt;Research Directions&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;&lt;strong&gt;Graph Stream Computing&lt;/strong&gt;: Distributed triangle counting and subgraph matching algorithms in streaming environments&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Social Network Optimization&lt;/strong&gt;: Game-theoretic social welfare control and incentive mechanisms in vehicular crowdsensing&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Personalized Recommendation&lt;/strong&gt;: Trip recommendation and route analysis based on graph attention auto-encoders&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Knowledge Graph Completion&lt;/strong&gt;: Knowledge representation-enhanced multimodal knowledge graph completion methods&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Data Fabric Storage&lt;/strong&gt;: Key technologies for data fabric distributed storage&lt;/li&gt;
&lt;/ul&gt;
&lt;h2 id="key-achievements"&gt;Key Achievements&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Proposed distributed streaming triangle counting framework (KBS 2023, ACM TKDD 2021)&lt;/li&gt;
&lt;li&gt;Proposed compact estimator for streaming triangle counting (IEEE TKDE 2024)&lt;/li&gt;
&lt;li&gt;Proposed unilateral control for social welfare in vehicular crowdsensing iterated games (JCST 2025)&lt;/li&gt;
&lt;li&gt;Proposed graph attention auto-encoder for personalized trip recommendation (KBS 2025, AAAI 2020)&lt;/li&gt;
&lt;li&gt;Proposed knowledge representation-enhanced multimodal knowledge graph completion (Computer Engineering and Applications 2025)&lt;/li&gt;
&lt;li&gt;Proposed social welfare control and free-riding incentives in cross-silo federated learning caching (ICASSP 2026)&lt;/li&gt;
&lt;/ul&gt;</description></item></channel></rss>